Spatial variability of heavy metal contents and contamination assessment in forest soils of Daxing'an Mountains
Bibliographic record
Abstract
Soil heavy metal pollution is a potential hazardous factor to forest health. However,few studies have conducted on heavy metal contents,spatial variability and pollution status of natural forest soils in Daxing'an Mountains. In the study,the contents of Cd,Cr,Pb,Cu,Zn,Ni,Hg and As in forest soils of Daxing'an Mountains were analyzed. The spatial variability of these heavy metal elements mentioned above and their pollution potential in the region were evaluated by using GIS spatial analysis combined with classic heavy metal pollution assessment methods. The results showed that:( 1) The spatial distributions of heavy metal contents exhibited moderate spatial heterogeneity,with variation coefficients from 16.67% to 35.39%. C0/( C0+C)values of Cd,Cr,Pb,Zn,Hg and As were less than 25%,suggesting that the spatial variability of their contents was mainly determined by structural factors,such as soil parent material and topography. C0/( C0+C) values of Cu and Ni varied in the range of 25%-75%,which means that these metals were mainly affected by non-structural factors and human activities. The distribution patterns of heavy metal contents in the region presented as patchy,banded and island modes.( 2) The contents of the eight heavy metals in the region showed a trend of accumulation. However,the average and maximum contents of the eight heavy metals were below the soil threshold levels of the Second Grade Criteria of the China's Environmental Quality Standard( GB 15618-1995). The maximum contents of Cu,Zn and As exceeded the soil threshold levels of the First Grade Criteria,and the maximum contents of the other five elements were below the soil threshold levels of the First Grade Criteria.( 3) As showed by the Geo-accumulation index,there was no pollution risk of Cr,Pb and Ni in the region,while the pollution risk of the other five elements was low. The Nemerow pollution index showed that slight pollution of heavy metals existed for overall soil quality in the region. Single factor ecological risk index showed that no potential risk was detected for Cu,Ni,Pb,Cr,Zn and As contents; however,the contents of Hg and Cd from some sites showed pollution risk. The content of Hg from some sites even reached the Third Pollution Level( moderate risk). The total potential ecological risk index of 80% samples in the study area was at the risk-free level,and that of 20% of the samples was at the general level of risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".